The subject matter discussed in the background section should not be assumed to be prior art merely as a result of its mention in the background section. Similarly, a problem mentioned in the background section or associated with the subject matter of the background section should not be assumed to have been previously recognized in the prior art. The subject matter in the background section merely represents different approaches, which in and of themselves may also be inventions.
A client-server model is a computing model which divides tasks between the providers of a resource or service, called servers, and resource or service requesters, called clients. Clients and servers communicate over a computer network. Clients initiate communication sessions with servers which await incoming requests. Functions such as email exchange, web access, and database access are typically built on the client-server model.
Data science applications are almost always executed by servers. When artificial intelligence (A.I.) models are applied to an action that a user takes on a client, such as to provide a recommendation or personalization, the flow is almost always the following: After a user of a client performs an action, a server identifies the user action, applies a pre-computed machine learning model to the user action, and provides the model's result synchronously or asynchronously to the user. Whereas this flow is unavoidable for complex data science applications, in a relatively lighter implementation on websites, the application of models can be executed on clients themselves, thereby freeing up server resources. In an example of a client-delegated intelligence approach for a website, a server creates models and encapsulates the models in resources, and clients download those resources when visiting the relevant servers' websites. As a user of a client performs actions and interacts with the website in the client's session, the client passes the session state through the downloaded model, thereby triggering the desired action for the user, with all of the model's logic executing entirely in the user's client.